Fix unreachable branch

.github/workflows/test.yml

@@ -12,8 +12,6 @@ jobs:
         BACKEND: ['numpy', 'pytorch', 'paddle']
         python-version: ['3.12']
         include:
-          - BACKEND: 'numpy'
-            python-version: '3.8'
           - BACKEND: 'numpy'
             python-version: '3.9'
             TENSORLY_TENALG_BACKEND: ['einsum']
@@ -67,7 +65,7 @@ jobs:
         TENSORLY_BACKEND=${{matrix.BACKEND}} pytest -vv --cov tensorly --cov-report xml --durations=10 tensorly
 
     - name: Check coverage with CodeCov
-      uses: codecov/codecov-action@v3
+      uses: codecov/codecov-action@v4
       with:
         file: ./coverage.xml
         verbose: true

tensorly/backend/__init__.py

@@ -21,14 +21,11 @@ class dynamically_dispatched_class_attribute(object):
 
     __slots__ = ["name"]
 
-    def __init__(self, name):
+    def __init__(self, name: str):
         self.name = name
 
-    def __get__(self, instance, cls=None):
-        if isinstance is None:
-            return getattr(cls.current_backend(), self.name)
-        else:
-            return getattr(instance.current_backend(), self.name)
+    def __get__(self, instance: types.ModuleType):
+        return getattr(instance.current_backend(), self.name)
 
 
 class BackendManager(types.ModuleType):

tensorly/decomposition/tests/test_tr_als.py

@@ -196,7 +196,7 @@ def test_tensor_ring_als_sampled_large_decomp(uniform_sampling, randomized_error
 
     # Some decomposition properties
     n_samples = 2000  # Note: The smallest least squares problem has 17160 rows
-    n_iter_max = 100
+    n_iter_max = 60
 
     # Generate random tensor which has exact tensor ring decomposition
     tensor = random_tr(